Research • Published Author • Outreach
I contributed to an AIAA publication on quadrotor performance and noise prediction using CHARM and PSU-WOPWOP for UAM. I also supported the NASA ULI UAM workshop in Daytona and led the Tello drone activity for students.
Published Research
This paper highlights mid-fidelity prediction of quadrotor performance and tonal noise, comparing simulation results against NASA experimental data. My work in the lab supported the blade geometry processing and thickness-noise analysis that contributed to the final results.
Mobility (UAM) vehicle and drone delivery industries. Rapid trend prediction of performance and noise is useful during the design phase of any vehicle and is necessary for informing advanced vehicle control. The simulation tool CHARM coupled to PSU-WOPWOP offers a mid-fidelity prediction capability applicable to these industries. Its ability to capture the performance and noise trends for the SUI Endurance small quadrotor is presented. The effect of some of the software’s modeling parameters is investigated. Traditional convergence is not obtained for some parameters. Still force and moment predictions are shown to be mostly within 5% and 10% respectively and the main tonal noise predictions are within 1dB of each other. When compared to performance and noise data from NASA experiments, trends are captured while the moment values are inaccurate. When focusing on the tonal noise, there is an underprediction of several dB. This is most likely because the wake interactions with other rotors are not fully modeled with the method.
Two Sides of UFMAL
Used CHARM with iterative tuning to predict drone force and moment performance, comparing results to NASA experimental data for validation.
Developed MATLAB tools to convert airfoil point data into STL models, enabling faster analysis across different blade geometries.
Analyzed thickness noise by comparing CAD-based airfoil data with CHARM predictions, building tools to streamline pressure and surface data processing.
Two Sides of UFMAL
Explored Embry-Riddle’s campus and got a closer look at its aerospace labs, aircraft, and engineering spaces.
Helped guide students through coding Tello drones, teaching them how to fly shapes, track colors, and recognize patterns.
Organized hands-on drone challenges where students flew through hoops, navigated obstacles, and completed precision landings.
Feel free to reach out for projects, collaboration, or opportunities.